National Diabetes Inpatient Audit Harms, 2019 England 13 November 2020

Annual report The National Diabetes Inpatient Audit – Harms (NaDIA-Harms) started in May 2018. It is designed to help reduce the serious inpatient harms identified by the NaDIA snapshot audits. Although there has been some reduction in the national point prevalence of both severe hypoglycaemia and inpatient-onset foot ulcers, they remain common; inpatient-onset diabetic ketoacidosis (DKA) and hyperosmolar hyperglycaemic state (HHS) rates have shown no improvement. Yet all these serious, potentially life-threatening events are largely preventable.

The NaDIA-Harms audit will enable trusts to identify and analyse local occurrences of these key inpatient harms, supporting local quality improvement (QI) work. By linking to the power of the core National Diabetes Audit (NDA), case-mix adjusted benchmarking will also be reported and risk-adjusted long term outcomes identified. Additionally, national characterisation of which patients are at highest risk will inform the development of better preventive care.

The hard work of all participants is hugely appreciated. Tracking these inpatient harms closely will allow a better understanding of how they occur, and help us to significantly improve safety for people with diabetes within the NHS.

Alistair Lumb, Clinical Lead, NaDIA-Harms Key details

This report covers four inpatient harms occurring in English hospitals in the 18 month period May 2018 to October 2019:

- Hypoglycaemic rescue
- DKA
- HHS
- Diabetic foot ulcer

The Welsh government chose not to participate in the NaDIA-Harms collection.

Acronyms and abbreviations

The following acronyms and abbreviations are used throughout the report and are not always defined on the slide where they appear:

- **BMI** = Body mass index

- **DFU** = Diabetic foot ulcer

- **DKA** = Diabetic ketoacidosis

- **HES** = Hospital Episode Statistics

- **HHS** = Hyperosmolar hyperglycaemic state

- **NaDIA** = National Diabetes Inpatient Audit

- **NDA** = National Diabetes Audit

- **RRT** = Renal replacement therapy Introduction: Overview

- The National Diabetes Inpatient Audit – Harms (NaDIA-Harms) is a **continuous** data collection to record serious inpatient events referred to as ‘harms’ that occur due to errors of inpatient diabetes management. The data collection started on 1 May 2018.

- The objective of NaDIA-Harms is to help reduce the rates of serious inpatient harms by providing hospitals with a system of case-mix adjusted benchmarked measurements.

- All acute hospitals in England should participate.

- The NaDIA-Harms audit is part of the National Diabetes Audit (NDA) programme within the National Clinical Audit and Patient Outcomes Programme (NCAPOP), commissioned by the Healthcare Quality Improvement Partnership (HQIP).

- This report covers NaDIA-Harms data collected between May 2018 and October 2019. Introduction: Why is the audit important?

NaDIA-Harms aims to monitor, and in time help reduce, instances of four life-threatening diabetes specific inpatient harms originally characterised in the NaDIA snapshot audits:

**Hypoglycaemic rescue**: A hypoglycaemic episode (a hypo) is a potentially dangerous drop in a patient’s blood glucose (BG) to below 4.0 mmol/L. Rescue treatment is required in severe cases of hypoglycaemia when the patient is either unconscious, too confused to follow instruction or unable to safely swallow because of danger of aspiration. Rescue treatment is applied using an injection of glucose or Glucagon. [?]

**DKA**: Diabetic ketoacidosis (DKA) mainly occurs in people with type 1 diabetes when a severe lack of insulin means the body cannot use glucose for energy and the body starts to break down other body tissue, releasing ketones as an alternative energy source. This can lead to life threatening ketoacidosis if the levels are too high. [?]

**HHS**: Hyperosmolar hyperglycaemic state (HHS) mainly occurs in people with type 2 diabetes who experience very high blood glucose levels (often over 40mmol/L). It can develop over a course of days or weeks through a combination of illness (e.g. infection) and dehydration and following high dose steroid therapy. [?]

**Diabetic foot ulcer**: Patients with diabetes are at a higher risk of developing foot lesions (ulcers) if they have diabetes associated blood flow (ischaemia) and nerve problems (neuropathy). [?]

A hospital inpatient whose BG levels are optimally managed should only very rarely experience a severe hypoglycaemic episode requiring rescue treatment.

The development of DKA after admission suggests that the inpatient’s insulin treatment was omitted, or insufficient levels of insulin were provided, for an appreciable time. DKA is a potentially life-threatening emergency which should not develop in hospital.

HHS is a potentially life-threatening emergency which should not develop in hospital.

Preventive care should stop new foot lesions developing in hospital.

These events are distressing, slow-down recovery, may be life-threatening and are entirely preventable. Introduction: Why is this report important?

Submission to NaDIA-Harms will contribute to efforts to reduce the rates of serious and avoidable inpatient harms. Data collected by NaDIA-Harms will facilitate local quality improvement work through the production of risk-adjusted outcomes and the identification of patients at risk.

What’s in the report?

This report includes: participation to date; the number of submissions of each inpatient harm; the estimated case ascertainment of each inpatient harm; and the patient profiles of people that experience each inpatient harm. The patient profiles include demographics, diabetes characteristics, treatment targets, care processes, admission characteristics and comorbidities.

The audit team appreciate the hard work of all submitters and recognise that it can initially be difficult to set up systems that record all inpatient harms. Introduction: NaDIA snapshot audit

Since 2010 information about the four inpatient harms has been collected in the NaDIA snapshot audit, which takes place on a given day in late September.

On the audit day, NaDIA 2019 found that:

- 1.4 per cent of inpatients with diabetes had required hypoglycaemic rescue in the last 7 days.
- 3.6 per cent with type 1 diabetes had developed DKA during their hospital stay.
- 0.2 per cent with type 2 diabetes had developed HHS during their hospital stay.
- 1.1 per cent had developed a diabetic foot ulcer during their hospital stay.

Changes over time: Whilst hypoglycaemic rescue and DFU both have reduced since the NaDIA snapshot began in 2010, similar reductions are not evident for DKA and HHS:

Requirements: The snapshot nature of the NaDIA collection, coupled with the relatively low incidence of the four inpatient harms, means that continuous collection via NaDIA-Harms is needed to allow robust monitoring at local level, and contribute to the drive to lower the incidence of these serious inpatient harms.

Comparability: For the first time, NaDIA snapshot figures have been adjusted for comparison against the number of cases in NaDIA-Harms. Estimated case ascertainment in NaDIA-Harms ranges from 20 per cent (DKA) to just 6 to 8 per cent (others). Details can be found in the Appendix. Key messages Key messages: Participation

Participation

All acute hospitals in England should participate in NaDIA-Harms. 100 NHS trusts have started to submit to the audit.

For comparison, 131 NHS trusts are known to be eligible for the NaDIA snapshot audit, meaning that NaDIA-Harms participation is around 76 per cent. 51 NHS trusts (39 per cent) are regular NaDIA-Harms submitters.

Case ascertainment

- 2,905 inpatient harms were submitted between May 2018 and October 2019 (18 months).
- Using estimates derived from the NaDIA 2019 snapshot, case ascertainment in NaDIA-Harms ranges from 6 (diabetic foot ulcer) to 20 per cent (DKA).

Recommendation 1: Acute hospitals should all participate in NaDIA-Harms, an important improvement initiative.

Notes: 1. One or more inpatient harm submission or any verified monthly nil submission in all six quarterly periods. Key messages: Higher risk characteristics

Higher risk characteristics

Characteristics that are consistently(^1) associated with higher rates of inpatient harms include:

- **White** ethnicity

- Current **smoker**

- Lower **BMI** (except DFU)

- **Type 1** diabetes

- Longer diabetes **duration**

- Impaired **renal function** (except DKA)

- **Emergency** (all) and **medical** (except DFU) admissions

- **Complications**: Admitted for **DKA** (except DFU), Admitted with diabetic foot disease, Heart failure (except DKA) and/or RRT required during admission

- Higher **HbA1c** and cholesterol

- Missing **treatment targets** and **care processes** in the audit year before admission

**Recommendation 2**: Healthcare professionals should be aware of the increased risk of harm in hospital inpatients with higher risk characteristics.

**Notes**: 1. Where the same statistically significant difference vs the inpatient population with diabetes at the 0.05 level was found in at least two of the three inpatient harms tested. HHS was excluded from testing due to the small number of episodes reported (80). Key messages: Comments

- NaDIA-Harms is a new audit involving continuous data collection.
- Setting up processes to identify and collect each inpatient harm has been a challenge, accounting for the under-reporting compared with estimates based on the NaDIA snapshot audit.
- The National Diabetes Foot Audit (NDFA) also involves continuous data collection, and data collection started from a relatively low starting point.
- The NDFA now captures an estimated 30 per cent of foot ulcers, and has already revealed very valuable insights into the association between structures of care and outcomes, leading to changes in practice.
- NaDIA-Harms has already revealed links between patient characteristics held in the core National Diabetes Audit (NDA) and the development of inpatient Harms.
- These characteristics could be used to identify on admission those at risk of significant harm, allowing appropriate interventions to be put in place to mitigate that risk.” Participation Participation: Overview

Audit questions: How many NHS trusts participated in the 2019 NaDIA-Harms audit? How many serious inpatient harms were recorded?

How is data collected? The NaDIA-Harms collection opened in May 2018. NHS trusts in England are encouraged to report instances (NHS number, date, hospital site) of four serious inpatient harms (hypoglycaemic rescue, DKA, HHS, diabetic foot ulcer) that had developed during the inpatient’s stay. Trusts can also record confirmation that no inpatient harms have occurred during a calendar month.

Why is this important? These inpatient harms are preventable. NaDIA-Harms will provide case-mix adjusted, benchmarked measurements and risk scores to facilitate local quality improvement work.

Key findings

- 108 NHS trusts in England have registered for the NaDIA-Harms audit.
- 100 NHS trusts in England have participated in the audit and 51 submitted in every quarterly period since inception (May 2018).

Context: 131 NHS trusts are known to be eligible for NaDIA snapshot, meaning that NaDIA-Harms participation is around 76 per cent.

Estimated case ascertainment in NaDIA-Harms ranges from 20 per cent (DKA) to just 6 to 8 per cent (others) – see Appendix.

Notes: 1. One or more inpatient harm submission or any verified monthly nil submission. 2. One or more inpatient harm submission or any verified monthly nil submission in all six quarterly periods. 3. Eligibility inferred from NaDIA snapshot participation (2015-19). Participation: Submitters

131 NHS trusts in England known to be eligible(^1) for NaDIA snapshot

108 registered for NaDIA-Harms

31 participants

100 NaDIA snapshot

100 NaDIA-Harms

51 regularly submitting(^3) to NaDIA-Harms

Notes: 1. Eligibility inferred from NaDIA snapshot participation (2015-19). 2. One or more inpatient harm submission or any verified monthly nil submission. 3. As for note 2, in each quarterly period. Findings

- When compared to the number of NHS trusts known to be eligible for the NaDIA snapshot, NaDIA-Harms participation is around **76 per cent** (100 of 131).
- The number of participants has **not risen** substantially despite an initial increase.

Notes: 1. One or more inpatient harm submission or any verified monthly nil submission in the quarterly period. Participation: Submissions over time

Figure 2: Number of episodes, by inpatient harm, England, May 2018 - October 2019 (rounded)

Table 1: Number of episodes, by inpatient harm, by quarterly period that inpatient harm occurred, England, May 2018 - October 2019 (rounded)

| Inpatient harm | May - Jul 2018 | Aug - Oct 2018 | Nov 2018 - Jan 2019 | Feb - Apr 2019 | May - Jul 2019 | Aug - Oct 2019 | Total | |--------------------------------|----------------|----------------|---------------------|----------------|----------------|----------------|---------| | Hypoglycaemic rescue [?] | 210 | 340 | 445 | 405 | 350 | 300 | 2,055 | | DKA [?] | 50 | 85 | 80 | 80 | 70 | 75 | 440 | | HHS [?] | 5 | 15 | 25 | 15 | 15 | 10 | 80 | | Diabetic foot ulcer [?] | 55 | 50 | 60 | 70 | 50 | 40 | 330 | | Total | 325 | 490 | 610 | 570 | 485 | 425 | 2,905 |

Context As this is a new data collection, quarterly changes in the rate of inpatient harms may reflect participation trends rather than real changes in incidence.

Notes: 1. Counts have been rounded. Counts between 1 and 7 are represented as a 5. All counts greater than 7 have been rounded to the nearest five. Consequently the total will not usually match the sum of the four constituent inpatient harms. Patient profiles Patient profiles: Overview

Audit questions: Are particular individual characteristics associated with a greater risk of inpatient harm?

How is data collected? Inpatient harms are identified and notified by hospital teams. Patient demographics, diabetes characteristics, treatment targets and care processes are linked from the core National Diabetes Audit (NDA). Hospital admission characteristics and comorbidities are linked from Hospital Episode Statistics (HES).

Why is this important? A better understanding of high risk features might help target preventive care. In the future such understanding will also permit calculation of case-mix adjusted rates.

Key findings NaDIA-Harms successfully linked to core NDA (93 per cent) and HES (88 per cent).

Higher risk characteristics found for all three inpatient harms(^1) tested were:

- **White** ethnicity
- **Type 1** diabetes
- Longer diabetes **duration**
- Higher **HbA1c**
- Missing **treatment targets** and **care processes** in audit year before admission
- **Emergency** admission
- **Complications during admission:** Admitted **with** foot disease, RRT required during admission

Results for HHS have not been included due to the small number of episodes reported (80).

Notes: 1. A statistically significant difference vs the inpatient population with diabetes at the 0.05 level in all three inpatient harms tested. HHS was excluded from testing due to the small number of episodes reported (80). Patient profiles: NaDIA-Harms linkage

To produce the patient profiles, NaDIA-Harms data was enriched by linkage:

**NaDIA-Harms**

- Hypoglycaemic rescue
- DKA
- HHS
- Diabetic foot ulcer

**Filters:** Date of inpatient harm during period: May 2018 to Oct 2019

**Hospital Episode Statistics (HES)**

- Admission method/ type
  - Cardiovascular complications:
    - Angina
    - Myocardial infarction
    - Heart failure
    - Stroke
  - Diabetes-specific complications:
    - Required renal replacement therapy
    - Admitted for DKA
    - Admitted with diabetic foot disease

**Filters:**

- HES episode classed as finished
- Inpatient admissions only – day cases, same-day discharges and regular day/night attendances are excluded

**Core National Diabetes Audit (NDA)**

- Age at start of NDA year
- Sex
- Ethnicity
- Diabetes type
- Diabetes duration at start of NDA year
- Smoking status
- Body mass index
- Renal function
- Deprivation quintile
- Treatment targets
- Care processes

**Filters:**

1. From the core NDA demographics table.
2. Taking the value closest to the inpatient harm date (in corresponding NDA year or one of the preceding three years).
3. Taking the value from the NDA year preceding the inpatient harm year (defined as Apr-Mar).

**Notes:**

- Using the start of the NDA year (defined as 1 April) rather than the actual inpatient harm date allows comparison with the NDA population.

% linked to NDA: 7.2 % linked to HES: 12.1

92.8 linked 87.9 linked Patient profiles: Inpatient population

Linkage was also used to produce a comparison population of inpatients with diabetes to compare with the profile of inpatients with inpatient harms recorded:

Core National Diabetes Audit (NDA) 2018-19

- Age at start of NDA year
- Sex
- Ethnicity
- Diabetes type
- Diabetes duration at start of NDA year
- Smoking status
- Body mass index
- Renal function
- Deprivation quintile
- Treatment targets
- Care processes

Filters: 1. From the core NDA demographics table. 2. Taking the value from NDA 2018-19. 3. Taking the value from the preceding NDA year i.e. NDA 2017-18.

Hospital Episode Statistics (HES) 2018-19

- Nights in hospital (Length of stay, LOS)
- Admission method/type
- Cardiovascular complications:
  - Angina
  - Myocardial infarction
  - Heart failure
  - Stroke
- Diabetes-specific complications:
  - Required renal replacement therapy
  - Admitted for DKA
  - Admitted with diabetic foot disease

Filters: 1. HES episode classed as finished 2. Inpatient admissions only – day cases, same-day discharges and regular day/night attendances are excluded. 3. Aged 17+ on admission. 4. Diagnosed with diabetes in the NDA on or before the admission start date. 5. Hospital days where any of the four inpatient harms occurred are excluded.

Comparison: Inpatient population with diabetes 2018-19 Characteristics of the inpatient population during 2018-19, adjusted for nights in hospital e.g. 1 night is counted once, 7 nights are counted 7 times etc.

### Table 2: Summary of characteristics associated with each inpatient harm

England, May 2018 - October 2019

| Characteristic | Hypoglycaemic rescue | DKA | Diabetic foot ulcer | |--------------------------------|----------------------|-----|---------------------| | **Demographics** | | | | | Age | Younger | Older| | | Sex | Female | Male | | | Ethnicity | White | White| | | Smoking | Current | Current| | | Deprivation | Least | | | | BMI | Lower | Lower| | | **Diabetes characteristics** | | | | | Diabetes type | Type 1 | Type 1| Type 1 | | Diabetes duration | Longer | Longer| Longer | | Renal function | Worse | Better| Worse | | **Treatment targets and care processes** | | | | | Blood pressure | | | | | Cholesterol | Higher | Higher| | | HbA1c | Higher | Higher| | | Met 3 treatment targets | Lower | Lower| Lower | | All 8 care processes | Lower | Lower| Lower | | **Hospital admissions** | | | | | Admission method | Emergency | Emergency| Emergency | | Admission type | Medical | Medical| Surgical | | **Complications during admission:** | | | | | No associations with Angina, Myocardial infarction or Stroke | | | | | Admitted for DKA | | | | | Admitted with foot disease | | | | | Heart failure | | | | | RRT required | | | |

**Key:**

- A characteristic is in **bold** where the same statistically significant difference vs the inpatient population with diabetes at the 0.05 level was found in at least two of the three inpatient harms tested.
- A trend (e.g. older / younger) is *italicised* where only found to be significant for one of the three inpatient harms tested.

**Notes:** 2. See Patient profiles: Endnotes.

HHS has not been included in the table due to the small number of episodes reported (80). Patient profiles: Hypoglycaemic rescue

Compared to the total population of inpatients with diabetes, people submitted to NaDIA-Harms who experienced hypoglycaemic rescue in hospital were:

- More likely to be ethnically White (88 vs 84 per cent)
- More likely to have type 1 diabetes (35 vs 9 per cent)
- Likely to have had diabetes for longer (median 18 vs 11 years)
- More likely to be a current smoker (18 vs 13 per cent)
- Likely to have impaired renal function (median eGFR 60 vs 69)
- Less likely to be in the most deprived quintile (23 vs 26 per cent)
- Likely to have a lower BMI (median 26 vs 28)

In the audit year before admission:

- More likely to have HbA1c >58 mmol/mol (74 vs 44 per cent)
- More likely to have cholesterol ≥ 5 mmol/L (35 vs 31 per cent)
- More likely to have missed one or more treatment target (85 vs 68 per cent)
- More likely to have missed one or more care process (60 vs 52 per cent) Patient profiles: DKA

Compared to the total population of inpatients with diabetes, people submitted to NaDIA-Harms who developed DKA in hospital were:

- Likely to be younger (median 67 vs 74 years)
- More likely to be female (52 vs 48 per cent)
- More likely to be ethnically White (94 vs 84 per cent)
- More likely to have type 1 diabetes (67 vs 9 per cent)
- Likely to have had diabetes for longer (22 vs 11 years)
- More likely to be a current smoker (21 vs 13 per cent)
- Less likely to have impaired renal function (median eGFR 78 vs 69)
- Likely to have a lower BMI (median 25 vs 28)
- More likely to be admitted as an emergency (91 vs 81 per cent)
- More likely to be a medical admission (71 vs 67 per cent)
- More likely to be admitted for DKA (55 vs 1 per cent)
- Less likely to have heart failure during admission (12 vs 19 per cent)
- More likely to require RRT (8 vs 4 per cent) during admission

In the audit year before admission:

- More likely to have HbA1c >58 mmol/mol (74 vs 44 per cent)
- More likely to have cholesterol ≥ 5 mmol/L (41 vs 31 per cent)
- More likely to have missed one or more treatment target (93 vs 68 per cent)
- More likely to have missed one or more care process (61 vs 52 per cent) Patient profiles: Diabetic foot lesion

Compared to the total population of inpatients with diabetes, people submitted to NaDIA-Harms who developed a diabetic foot lesion in hospital were:

- Likely to be older (median 77 vs 74 years)
- More likely to be male (63 vs 52 per cent)
- More likely to be ethnically White (91 vs 84 per cent)
- More likely to have type 1 diabetes (15 vs 9 per cent)
- Likely to have had diabetes for longer (median 15 vs 11 years)
- Likely to have impaired renal function (median eGFR 59 vs 69)
- More likely to be admitted as an emergency (88 vs 82 per cent)
- More likely to be a surgical admission (33 vs 25 per cent)
- More likely to have been admitted with diabetic foot disease (14 vs 6 per cent)
- More likely to require RRT (9 vs 5 per cent) during admission
- More likely to have heart failure during admission (31 vs 19 per cent)

In the audit year before admission:

- More likely to have HbA1c >58 mmol/mol (51 vs 44 per cent)
- More likely to have missed one or more treatment target (74 vs 68 per cent)
- More likely to have missed one or more care process (63 vs 52 per cent)

### Table 3: Patient demographics(^1), by inpatient harm(^2),

Inpatient harms: England, May 2018 - October 2019. Inpatient population: England, 2018-19 (rounded(^3))

| Group | Age(^6) | Sex | Ethnicity | Smoking status | Deprivation quintile | BMI | |--------------------------------------------|------------|-----|-----------|-----------------|----------------------|-----| | | Median | Male | Female | White | Non-white | Current smoker | Ex-smoker | Non-smoker(^7) | Most deprived | Least deprived | Significance | Median | | Inpatient population with diabetes(^4) | 74.0 | 52.5 | 47.5 | 84.1 | 15.9 | 12.9 | 39.2 | 47.8 | 26.0 | 14.2 | | 28.2 | | Hypoglycaemic rescue(^5) | 74.0 | n | 51.4 | 48.6 | n | 88.2 | 11.5 | * | 17.9 | 35.4 | * | 22.9 | | DKA(^6) | 67.0 | * | 47.8 | 52.2 | * | 94.0 | 6.0 | * | 21.1 | 30.0 | 48.9 | 24.7 | | Inpatient population with diabetes(^5) | 74.0 | 52.3 | 47.7 | 84.3 | 15.7 | 12.7 | 39.1 | 48.2 | 25.9 | 14.3 | | 28.0 | | Diabetic foot ulcer(^7) | 77.0 | * | 63.3 | 35.0 | * | 90.7 | 9.3 | * | 12.1 | 41.4 | 46.6 | n |

**Findings:** Higher risk characteristics(^11) for inpatient harms include:

- **White** ethnicity
- Being a **current smoker** (except DFU)
- Lower **BMI** (except DFU)

HHS has not been included in the table due to the small number of episodes reported (80).

**Notes:** Significance vs. inpatient population with diabetes: * = statistically significant at the 0.05 level. n = not statistically significant. Proportions are tested using the Chi-squared test. Medians are tested using the Mann–Whitney U test. 1. Cases with missing or unknown values are excluded from the calculations. The proportions of the inpatient population (data row 1) with missing or unknown values are: Age 0.0%; Sex 0.2%; Ethnicity 9.7%; Smoking status 4.9%; Deprivation quintile 5.7%; BMI 29.2%. 2, 3, 4, 5, 6, 7, 11. See Patient profiles: Endnotes.

## Patient profiles: Diabetes characteristics

### Table 4: Diabetes characteristics(^1), by inpatient harm(^2),

Inpatient harms: England, May 2018 - October 2019. Inpatient population: England, 2018-19 (rounded(^3))

| Group | Diabetes type | Diabetes duration(^6) | Renal function eGFR ([\\text{ml/min/1.73m}^2]) | |--------------------------------------------|---------------|-------------------------|-----------------------------------------------| | | Type 1 | Type 2 | Median | Median | | Inpatient population with diabetes(^4) | 8.8 | 91.2 | 11.0 | 69.4 | | Hypoglycaemic rescue ([?]) | 34.7 | 65.3 | * | 59.5 | | DKA ([?]) | 67.4 | 32.6 | * | 78.1 | | Inpatient population with diabetes(^5) | 8.5 | 91.5 | 11.0 | 68.6 | | Diabetic foot ulcer ([?]) | 15.0 | 85.0 | * | 59.4 |

### Findings

Higher risk characteristics(^11) for inpatient harms include:

- Diabetes **type 1**
- Longer diabetes **duration**
- Impaired **renal function** (except DKA)

HHS has not been included in the table due to the small number of episodes reported (80).

### Notes

Significance vs. inpatient population with diabetes: * = statistically significant at the 0.05 level. n = not statistically significant.

Proportions are tested using the Chi-squared test. Medians are tested using the Mann–Whitney U test.

1. Cases with missing or unknown values are excluded from the calculations.

The proportions of the inpatient population (data row 1) with missing or unknown values are:

- Diabetes type 2.3%; Diabetes duration 0.0%; eGFR 12.4%.

2, 3, 4, 5, 6, 11. See Patient profiles: Endnotes. Patient profiles: Treatment targets and care processes

Table 5: Treatment targets and care processes in the audit year preceding hospital admission(^1,8), by inpatient harm(^2), Inpatient harms: England, May 2018 - October 2019. Inpatient population: England, 2018-19 (rounded(^3))

| Group | Treatment targets(^8) ([?]) in year prior to admission | Received all 8 care processes(^8) ([?]) in year prior to admission | |--------------------------------------------|-------------------------------------------------------------|---------------------------------------------------------------------| | | Blood pressure (≤ 140/80) | Cholesterol (< 5 mmol/L) | HbA1c (≤ 58 mmol/mol)(^4) | Met all 3 treatment targets | % | % | % | % | | Inpatient population with diabetes(^4) ([?]) | 69.6 | 68.9 | 56.6 | 32.4 | 48.0 | | Hypoglycaemic rescue ([?]) | 69.9 | n | 65.4 | * | 25.8 | * | 14.9 | * | 39.6 | * | | DKA ([?]) | 72.7 | n | 59.1 | * | 14.8 | * | 6.8 | * | 38.6 | * | | Inpatient population with diabetes(^5) (LOS≥3) ([?]) | 69.5 | 68.9 | 56.6 | 32.3 | 47.1 | | Diabetic foot ulcer ([?]) | 64.9 | n | 71.9 | n | 49.1 | * | 26.3 | * | 36.8 | * |

Findings: Higher risk characteristics(^11) for inpatient harms include:

- Higher HbA1c in the audit year prior to admission
- Not meeting all 3 treatment targets in the audit year prior to admission
- Not having all 8 care processes in the audit year prior to admission

Notes: Significance vs. inpatient population with diabetes: * = statistically significant at the 0.05 level. n = not statistically significant. 1. Cases with missing or unknown values are excluded from the calculations. The proportions of the inpatient population (data row 1) with missing or unknown values are: 5.9% (all values). 2, 3, 4, 5, 8, 11. See Patient profiles: Endnotes.

### Table 6: Hospital admission method and main speciality(^1), by inpatient harm(^2),

Inpatient harms: England, May 2018 - October 2019. Inpatient population: England, 2018-19 (rounded(^3))

| Group | Admission method | Admission type | |--------------------------------------------|------------------|----------------| | | Emergency | Elective | Other(^a) | Medical | Surgical | Other(^a) | | Inpatient population with diabetes(^4) [?] | 81.1 | 12.4 | 6.5 | 67.4 | 26.3 | 6.5 | | Hypoglycaemic rescue [?] | 93.6 | 3.2 | 3.2 | * | 78.7 | 20.7 | 0.5 | | DKA [?] | 91.0 | 7.7 | 2.6 | * | 70.5 | 29.5 | 1.3 | | Inpatient population with diabetes(^5) (LOS≥3) [?] | 81.7 | 11.1 | 7.2 | 67.7 | 24.7 | 7.8 | | Diabetic foot ulcer [?] | 87.9 | 5.2 | 6.9 | * | 65.5 | 32.8 | 1.7 |

**Findings:** Higher risk characteristics(^11) for inpatient harms include:

- **Emergency** admission
- **Medical** admission (except DFU)

HHS has not been included in the table due to the small number of episodes reported (80).

**Notes:** Significance vs. inpatient population with diabetes: * = statistically significant at the 0.05 level. n = not statistically significant. Proportions are tested using the Chi-squared test.

1. Cases with missing or unknown values are excluded from the calculations.
2. The proportions of the inpatient population (data row 1) with missing or unknown values are:
   - Admission method 0.0%; Admission type 0.2%.
3. See Patient profiles: Endnotes.

### Table 7: Complications during hospital admission, by inpatient harm

Inpatient harms: England, May 2018 - October 2019. Inpatient population: England, 2018-19 (rounded)

| Group | Cardiovascular complications (at any point during admission) | Diabetes-specific complications (at specified point during admission) | |--------------------------------------------|-------------------------------------------------------------|---------------------------------------------------------------------| | | Angina | Myocardial infarction | Heart failure | Stroke | Admitted for DKA | Admitted with diabetic foot disease | RRT required during admission | | Inpatient population with diabetes[^4] | 7.9 | 3.7 | 18.5 | 6.7 | 1.1 | 5.8 | 4.4 | | Hypoglycaemic rescue[^2] | 6.9 n | 4.5 n | 25.3 * | 6.6 n | 10.4 * | 8.0 * | 7.2 * | | DKA[^2] | 6.4 n | 5.1 n | 11.5 * | 7.7 n | 55.1 * | 6.4 * | 7.7 * | | Inpatient population with diabetes[^5] | 7.6 | 3.7 | 19.5 | 7.5 | 0.9 | 6.4 | 4.7 | | Diabetic foot ulcer[^2] | 6.9 n | 5.2 n | 31.0 * | 6.9 n | 3.4 | 13.8 * | 8.6 * |

**Findings:** Higher risk characteristics[^11] for inpatient harms include:

- **Cardiovascular complications:** Heart failure during admission (except DKA)
- **Diabetes-specific complications:** Admitted for DKA, Admitted with diabetic foot disease, RRT required during admission

______________________________________________________________________

**Notes:** * = statistically significant at the 0.05 level (vs. inpatient population with diabetes). n = not statistically significant (vs. Inpatient population with diabetes). 2, 3, 4, 5, 10, 11. See Patient profiles: Endnotes. Patient profiles: Endnotes

01. Endnote 1 is specific to each table and the notes are listed beneath the individual tables.
02. HHS has not been included in the table due to the small number of episodes reported (80).
03. Percentages are derived from rounded values. Underlying counts between 1 and 7 are set to 5. All counts greater than 7 are rounded to the nearest five. Consequently some percentages may not sum up to exactly 100 per cent.
04. Proportions for the inpatient population with diabetes are calculated using the sum of nights in hospital during 2018-19 for people with diabetes in NDA 2018-19, where diabetes was diagnosed on or before admission. Day cases and same-day discharges are counted as zero days and are therefore excluded. Patients with diabetes recorded in HES 2018-19 that are not in NDA 2018-19 are excluded. Medians are calculated using the value on admission, counted once for each night in hospital. For further information, see: Patient profiles: Inpatient population.
05. See note 4 above, with additional exclusion for admissions that are less than 3 nights due to the audit requirement that new onset foot ulcers must occur more than 72 hours after admission.
06. Calculated using the start of the NDA audit year (defined as 1 April for this report) rather than the actual inpatient harm date allows comparison with the total NDA population.
07. Group comprises of non-smokers whose history is unknown and patients who have never smoked.
08. Treatment target and care process information is taken from the NDA audit year prior to the hospital admission (e.g. from 2017-18 where the hospital admission is in 2018-19).
09. The category ‘Other’ covers: Admission methods ‘Maternity’ and ‘Other’; Admission types ‘Other’, ‘Pathology’, ‘Psychiatry’ and ‘Radiology’.
10. Complication recorded at any point during the admission, except: ‘Admitted for DKA’ and ‘Admitted with diabetic foot disease’.
11. Where the same statistically significant difference vs the inpatient population with diabetes at the 0.05 level was found in at least two of the three inpatient harms tested. HHS was excluded from testing due to the small number of episodes reported (80). Appendix: Case ascertainment Appendix: Case ascertainment

Overview

Audit questions What is the case ascertainment (completeness) for DKA, HHS, foot ulcers and hypoglycaemic rescue in NaDIA-Harms?

How is data collected? Case ascertainment for each type of inpatient harm in NaDIA-Harms was calculated using estimates derived from the 2019 NaDIA snapshot. The full methodology and breakdown of the figures can be found on the following slides 33 to 35.

The NaDIA snapshot audit was performed on a nominated day between 23 and 27 September 2019. Participating hospital teams identified all inpatients with diabetes. Where the patient was able and willing a Bedside Audit form was completed which provided information on the patient’s medical treatment (including any inpatient harms experienced during their stay) taken from the patient’s notes.

Why is this important? The snapshot nature of the main NaDIA collection, combined with the low incidence of the four inpatient harms, means that continuous collection is necessary to enable robust monitoring at local level.

In tandem, the NaDIA snapshot can be used to assess to what extent NaDIA-Harms is capturing inpatient harm information within England.

Context 2,905 inpatient harms were submitted to NaDIA-Harms between May 2018 and October 2019 (18 months). The majority were hypoglycaemic rescue (2,055).

Key findings Estimated case ascertainment in NaDIA-Harms ranges from 20 per cent (DKA) to just 6 to 8 per cent (others) Appendix: Case ascertainment

DKA

Methodology

• In the 2019 NaDIA snapshot(^1) there were 53 cases of hospital-acquired DKA(^3) reported over 195,380 days in hospital(^4), equating to a rate of 0.00027 cases of DKA per day per inpatient with diabetes.

• Across the English population of 14,500 inpatients with diabetes on a given day, this approximates to 3.9 cases of DKA per day, 1,437 per year or 2,159 scaled to the duration of the NaDIA-Harms audit (549 days).

The 440 cases of DKA in NaDIA-Harms(^2) are therefore estimated to be around 20 per cent of the estimated total cases.

Notes: 1. The 2019 NaDIA snapshot was undertaken by participating hospital teams on a nominated day between 23 and 27 September 2019. 2. NaDIA-Harms figures have been rounded to the nearest 5. 3. NaDIA 2019 Bedside Audit Q21: ‘Did the patient develop DKA at any time after their admission?’ Note that only one instance of DKA per patient is recorded, whereas NaDIA-Harms can collect multiple instances per patient. 4. NaDIA 2019 Bedside Audit Q9: ‘Number of nights in hospital?’ is used as a proxy for the number of days in hospital. Appendix: Case ascertainment HHS and Diabetic foot ulcer

Figure 4: Case ascertainment for: HHS(^2,3,5), (^[?]) England, May 2018 - October 2019

NaDIA-Harms 7.6%

Estimated: 1,059 Submitted: 80

Figure 5: Case ascertainment for: diabetic foot ulcer(^2,4,5), (^[?]) England, May 2018 - October 2019

NaDIA-Harms 6.4%

Estimated: 5,128 Submitted: 330

Notes: 1. The 2019 NaDIA snapshot was undertaken by participating hospital teams on a nominated day between 23 and 27 September 2019. 2. NaDIA-Harms figures have been rounded to the nearest 5. 3. NaDIA 2019 Bedside Audit Q21: ‘Did the patient develop HHS at any time after their admission?’ Note that only one instance of HHS per patient is recorded, whereas NaDIA-Harms can collect multiple instances per patient. 4. NaDIA 2019 Bedside Audit Q40: ‘Did a new foot lesion/ulcer (e.g. heel ulcer) arise during this admission?’ Note that only one instance of diabetic foot ulcer per patient is recorded, whereas NaDIA-Harms can collect multiple instances per patient. 5. NaDIA 2019 Bedside Audit Q9: ‘Number of nights in hospital?’ used as a proxy for the number of days in hospital.

Methodology Case ascertainment for HHS and diabetic foot ulcer is calculated using the same methodology as for DKA. Appendix: Case ascertainment

Hypoglycaemic rescue

Methodology

The 2019 NaDIA snapshot(^1) recorded whether the inpatient experienced DKA, HHS or diabetic foot ulcer at any point during their hospital stay. In contrast, the snapshot recorded the total number of cases of hypoglycaemic rescue over the seven days prior to the audit(^3). The resultant figure was adjusted accordingly to ensure the collection periods were standardised(^4), resulting in estimated case ascertainment of seven per cent of total cases(^5).

Note that the 2019 NaDIA snapshot did not specify “rescue treatment” in the harm definition, which may impact the size of the estimate.

Figure 6: Case ascertainment for: hypoglycaemic rescue(^2,3,4,5), [?]

England, May 2018 - October 2019

Estimated: 29,213 Submitted: 2,055

Notes: 1. The 2019 NaDIA snapshot was undertaken by participating hospital teams on a nominated day between 23 and 27 September 2019. 2. NaDIA-Harms figures have been rounded to the nearest 5. 3. NaDIA 2019 Bedside Audit Q18: ‘Number of episodes of hypoglycaemia requiring injectable treatment (glucagon or IV glucose)?’ used as the count of hypoglycaemic rescues within the previous seven days of the inpatient’s stay. Bedside Audit Q13: ‘Is the glucose chart available for review?’ must also be ‘yes’ to be included in the hypoglycaemic rescue count. 4. NaDIA 2019 Bedside Audit Q9: ‘Number of nights in hospital?’ used as a proxy for the number of days in hospital, up to a maximum of seven days. 5. During the NaDIA-Harm data collection it became apparent that there was confusion about the exact definition of the hypoglycaemia harm that should be reported. The definition has been clarified on the NaDIA-Harms website (summarised on slide 37) and communication has also been made with those submitting data. This may have influenced the case ascertainment data for this harm. Glossary **Glossary:**

**Definitions: Hypoglycaemic rescue**

**Guidance** on harm specification questions within the NADIA-Harms data collection: **Hypoglycaemic rescue**

**Question:** ‘Did the patient require injectable rescue treatment for an episode of hypoglycaemia starting more than 6 hours after admission?’

For the purpose of this audit an episode should be recorded only if subcutaneous and/or intravenous injected rescue treatment (glucagon, glucose) for severe hypoglycaemia was used.

For consistency and compatibility this harm is defined **not** by the measured blood glucose level but by the need to urgently counteract **severe** hypoglycaemic symptoms such as loss of consciousness, acute confusion or seizures with injected treatment. Rescue treatment would usually be intravenous glucose or subcutaneous/ intramuscular/intravenous glucagon.

For example, these treatments may be required if pre-meal insulin had been given but the meal had not been delivered resulting in severe hypoglycaemic (loss of consciousness, acute confusion, seizures etc due to a low blood glucose) requiring rescue treatment.

Low blood glucose arising in patients receiving intravenous insulin infusions as well as intravenous glucose has led to some misunderstanding of ‘rescue treatment’. Intravenous glucose infusions should always run alongside continuous intravenous insulin and their use in this situation should **not** be considered ‘rescue treatment’ even when the CBG falls below 4.0 mmol/L **provided** that the patient has **no severe** hypoglycaemic symptoms. If, however, the person develops severe hypoglycaemic symptoms such as loss of consciousness, acute confusion or seizures during the infusion and require additional glucose or glucagon this would be considered ‘rescue treatment’. **Glossary:**

**Definition: DKA and HHS**

**Guidance** on harm specification questions within the NADIA-Harms data collection: **DKA**

**Question:** ‘Was the patient diagnosed with new onset DKA more than 24 hours after admission?’

DKA requires three key features for diagnosis:

- Known diabetes or blood glucose over 11.0 mmol/l.
- Ketonaemia (blood ketones 3.0 mmol/l or more) or urine ketones 2+ or more.
- Acidosis with venous pH less than 7.3 or bicarbonate less than 15 mmol/l.

For more on the definition of DKA please refer to the JBDS guidelines on the [ABCD web site](#).

**Guidance** on harm specification questions within the NADIA-Harms data collection: **HHS**

**Question:** ‘Was the patient diagnosed with new onset HHS more than 24 hours after admission?’

HHS has characteristic features used in its diagnosis:

- Hypovolaemia.
- Marked hyperglycaemia (blood glucose 30 mmol/l or more) without significant ketonaemia (blood ketones less than 3 mmol/l) or acidosis (venous pH 7.3 or more/bicarbonate 15 mmol/l or more).
- Osmolality usually 320 mosmol/kg or more.

For more on the definition of HHS please refer to the JBDS guidelines on the [ABCD web site](#). Glossary: Definition: Diabetic foot ulcer

**Guidance** on harm specification questions within the NADIA-Harms data collection: **Diabetic foot ulcer**

**Question:** ‘Was the patient diagnosed with a new onset foot ulcer more than 72 hours after admission?’

The audit is not intended to collect reports of foot ulcers that are present on admission, or which develop within 3 days of admission. Grade 2+ Pressure sores on the foot that develop more than 72 hours after admission should be included. Deep tissue injury which has not progressed to skin ulceration is not included. Traumatic skin foot lesions and foot infections which arise during the admission are included.

The definition of ‘Admitted with diabetic foot disease’ used in this report is discussed on slide 40.

For further information on the audit, visit the NaDIA-Harms homepage: [https://digital.nhs.uk/data-and-information/clinical-audits-and-registries/national-diabetes-in-patient-audit-nadia-harms](https://digital.nhs.uk/data-and-information/clinical-audits-and-registries/national-diabetes-in-patient-audit-nadia-harms) Glossary: Definition: Admitted with diabetic foot disease

**Diabetic foot disease** is defined as a foot affected by ulceration that is associated with neuropathy and/or peripheral arterial disease of the lower limb in a patient with diabetes(^1).

People with diabetic foot ulcers sometimes require admission to hospital to treat their foot disease. This occurs when the condition of the foot threatens survival of either the foot or the patient. Such deterioration is often a result of infection (requiring intravenous antibiotics, with or without local surgery) or poor arterial blood flow. Resultant hospital stays and rehabilitation may be lengthy. In extreme cases amputation is required.

To identify people admitted to hospital with diabetic foot disease, the first episode of each admission has been searched for the following **clinical procedures** or **diagnoses** predominantly associated with inpatient management of diabetes related foot disease(^2):

**Foot disease clinical diagnoses**

- Diabetes mellitus with peripheral circulatory complications
- Ulcer of the lower limb
- Decubitus ulcer
- Cellulitis
- Osteomyelitis
- Gangrene
- Atherosclerosis

**Foot disease clinical procedures**

- Debridement of a foot/leg wound
- Minor and major amputation of lower limb

______________________________________________________________________

**Notes:**

1. Alexiadou K., Doupis J. *Management of diabetic foot ulcers*. Diabetes Therapy. 2012;3:1–15. doi: 10.1007/s13300-012-0004-9.
2. Public Health England. Diabetic Foot Profiles. Technical Document. Note that patients may have other conditions which are contributing factors towards their hospital stay. Glossary: Definition: Care Processes

Care processes are reported on in the core National Diabetes Audit (NDA). The latest full NDA report into Care Processes and Treatment Targets covered the period 01 January 2017 to 31 March 2018.

NICE recommends that people with diabetes have all 8 of the following care processes at least once a year):

**Blood Pressure** is a measurement of the force driving the blood through the arteries. Blood pressure readings contain two figures, e.g. 130/80. The first is known as the systolic pressure which is produced when the heart contracts. The second is the diastolic pressure which is when the heart relaxes to refill with blood.

**BMI measurement** – Body Mass Index calculated from weight and height to classify under, normal, overweight and obese.

**Serum creatinine** – this blood test is used as measure kidney function.

**Urinary albumin** – this urine test detects the earliest stages of kidney disease.

**Cholesterol** – this blood test measures a type of fat that can damage blood vessels.

**Foot check** – this examination checks the blood supply and sensation (feeling) in the feet. Loss of either is a risk for foot disease.

**Smoking Status** – this records whether the person is a smoker. Smoking increases the diabetic risk for heart attacks and stroke.

**HbA1c** – this is a blood test for average blood glucose levels during the previous two to three months. Glossary: Definition: Treatment targets

Treatment targets are reported on in the core National Diabetes Audit (NDA). The latest full NDA report into Care Processes and Treatment Targets covered the period 01 January 2017 to 31 March 2018.

NICE(^1) defines the following target levels to reduce risks of complications for people with diabetes. Note that only the first three (highlighted in blue) are covered in this report:

- **HbA1c** – the closer this is to normal (less than 42 mmol/mol) the lower is the risk of all long term complications of diabetes. **NDA treatment target:** ≤ 58 mmol/mol.

- **Cholesterol** – reducing cholesterol levels lowers the risk of heart attacks and strokes. **NDA treatment target:** < 5 mmol/L.

- **Blood Pressure** – high levels are a risk for heart attacks and strokes; they also drive progression of eye and kidney disease. **NDA treatment target:** ≤ 140/80.

**Primary prevention of CVD** – The prescription of statins for people with diabetes aged 40 to 80 years with no history of heart disease to reduce the risk of cardiovascular disease.

**Secondary prevention of CVD** – The prescription of statins for people with diabetes (any age) with a history of heart disease to reduce the risk of cardiovascular disease.

**Combined prevention of CVD** – The prescription of statins for people with diabetes that fall into either of the primary or secondary prevention groups.

Notes: 1. NICE treatment target specifications were updated in 2015-16 and now differ between Type 1 and Type 2 diabetes ([https://www.nice.org.uk/guidance/ng17](https://www.nice.org.uk/guidance/ng17); [https://www.nice.org.uk/guidance/ng28](https://www.nice.org.uk/guidance/ng28)). Glossary: Estimated glomerular filtration rate(^1) (eGFR)

A patient's **estimated glomerular filtration rate** (eGFR) is used to determine how damaged their kidneys are, known as the stage of **chronic kidney disease** (CKD).

eGFR results are given as a stage from 1 of 5:

- **Stage 1** (G1) – a normal eGFR above 90ml/min, but other tests have detected signs of kidney damage
- **Stage 2** (G2) – a slightly reduced eGFR of 60 to 89ml/min, with other signs of kidney damage
- **Stage 3a** (G3a) – an eGFR of 45 to 59ml/min
- **Stage 3b** (G3b) – an eGFR of 30 to 44ml/min
- **Stage 4** (G4) – an eGFR of 15 to 29ml/min
- **Stage 5** (G5) – an eGFR below 15ml/min, meaning the kidneys have lost almost all of their function

**Notes:** 1. Information on this slide is adapted from: [https://www.nhs.uk/conditions/kidney-disease/diagnosis/](https://www.nhs.uk/conditions/kidney-disease/diagnosis/). Additional information Additional information: Future plans

Next steps

• Circulate this report to the inpatient diabetes community and promote the project to those not participating. • Write to the clinical teams not currently participating to identify their barriers and offer support. • Identify good practice from good submitters, create case studies and promote to other services.

Future plans

• Identify services with good practice to support other services in managing and reducing inpatient harms in patients with diabetes. The NaDIA-Harms team would like to thank all the people and teams who have worked hard to contribute to this unique and valuable insight into the inpatient care of people with diabetes.

Development and delivery of the NaDIA-Harms is guided by a multi-professional advisory group of clinicians and patient representatives, chaired by Alistair Lumb. The NaDIA-Harms Advisory Group members include:

- **Alistair Lumb** Consultant in Diabetes and Acute General Medicine and Clinical Lead for NaDIA-Harms, Oxford University Hospitals NHS Foundation Trust (Chair)

- **Gerry Rayman** Consultant Diabetologist and National Clinical Lead for Inpatient Diabetes

- **Bob Young** NDA Specialist Clinical Lead

- **Alex Berry** NDA Engagement Lead, Diabetes UK

- **Jodie Buckingham** MDFT Representative, Oxford

- **Sophie Colling** NDA Project Support Officer, Diabetes UK

- **Sowmya Gururaj-Setty** Consultant Endocrinologist, Northampton GH

- **Kath Higgins** Diabetes Consultant, Leicester’s Hospitals

- **AniAjit Kumar** Lead DSN, Calderdale Royal Hospital

- **Maureen McGinn** Patient Representative

- **Julie Michalowski** Audit Manager, NHS Digital

- **Rahul Nayar** Diabetes Consultant, South Tyneside & Sunderland NHS FT

- **Claire Neely** Diabetes Specialist Nurse, Kingston Hospital

- **Mayank Patel** Diabetes Consultant, UH Southampton

- **David Roberts** Patient Representative

- **Jonathan Thow** Consultant Endocrinologist, York Teaching Hospital

- **Andrew Whitehead** Audit Coordinator, NHS Digital

- **Emilia Woch** Higher Information Analyst, NHS Digital

- **Arthur Yelland** Senior Information Analyst, NHS Digital The Healthcare Quality Improvement Partnership (HQIP). The National Diabetes Inpatient Audit - Harms (NaDIA-Harms) audit is commissioned by the Healthcare Quality Improvement Partnership (HQIP) as part of the National Clinical Audit and Patient Outcomes Programme (NCAPOP). HQIP is led by a consortium of the Academy of Medical Royal Colleges, the Royal College of Nursing, and National Voices. Its aim is to promote quality improvement in patient outcomes, and in particular, to increase the impact that clinical audit, outcome review programmes and registries have on healthcare quality in England and Wales. HQIP holds the contract to commission, manage, and develop the National Clinical Audit and Patient Outcomes Programme (NCAPOP), comprising around 40 projects covering care provided to people with a wide range of medical, surgical and mental health conditions. The programme is funded by NHS England, the Welsh Government and, with some individual projects, other devolved administrations and crown dependencies [www.hqip.org.uk/national-programmes](http://www.hqip.org.uk/national-programmes).

NHS Digital is the new name for the Health and Social Care Information Centre. NHS Digital managed the publication of the 2018 annual report.

Diabetes UK is the largest organisation in the UK working for people with diabetes, funding research, campaigning and helping people live with the condition.

The National Cardiovascular Intelligence Network (NCVIN) is a partnership of leading national cardiovascular organisations which analyses information and data and turns it into meaningful timely health intelligence for commissioners, policy makers, clinicians and health professionals to improve services and outcomes.